Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models

Author:

Krivitsky Pavel N.ORCID

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference37 articles.

1. Asuncion, A.U., Liu, Q., Ihler, A.T., Smyth, P., 2010. Learning with blocks: Composite likelihood and contrastive divergence. In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10). URL http://machinelearning.wustl.edu/mlpapers/papers/AISTATS2010_AsuncionLIS10.

2. Spatial interaction and the statistical analysis of lattice systems (with discussion);Besag;J. R. Stat. Soc. Ser. B Stat. Methodol.,1974

3. On contrastive divergence learning;Carreira-Perpiñan,2005

4. Elements of Information Theory;Cover,1991

5. Fellows, I.E., 2014. Why (and when and how) contrastive divergence works. arXiv preprint arXiv:1405.0602.

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